Senior QA Engineer (5-8 years)

About the Role- We are looking for a highly skilled Tooling and AI Automation Engineer with 5-8 years of relevant experience to join our Automation team—not in a traditional application testing but as a specialist focused on building internal tools, test intelligence platforms, dashboards, and AI-driven test enablement frameworks. Required Skills: • Proficiency in Java / Python. • Experience in building REST APIs or microservices for internal use and building new testing frameworks from scratch. • Strong understanding of test automation frameworks (e.g., Pytest, Playwright, Cypress, Selenium ). • Solid Hands on experience in API Testing using Rest Assured , Mobile Automation using Appium(mandatory) and basics of Performance testing (good to have) • Working knowledge or experience with Mabl, TestRigor, or any AI automation tool . • Experience with GenAI or LLM integration for test case generation or failure analysis. • Experience integrating tools with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI). • Familiarity with databases (SQL, NoSQL) and working with test data at scale. • Good in Debugging, Test Case planning, problem solving and logical thinking. Key Responsibilities: • Test Automation Development: Build and maintain robust, scalable test automation frameworks for API, web, and mobile platforms. • Design, develop, and maintain internal tools that enhance automation capabilities, CI/CD integration, and test data visualization. • Build intelligent dashboards for real-time reporting of test results, release quality metrics, and defect analytics. • Develop AI/ML-based solutions to optimize test case prioritization, test suite reduction, flakiness prediction, and self-healing scripts. • Integrate tools and dashboards with CI pipelines (e.g., Jenkins, GitHub Actions) and test frameworks (Selenium, Playwright, etc.). • Work closely with SREs, and DevOps teams to ensure tools are scalable, performant, and well-adopted. • Create APIs, microservices, or CLI tools that support testing workflows, artifact management, and defect traceability. • Continuously evaluate new AI/ML advancements and incorporate them into test engineering practices